Examples/CurrentVoltageCurve/CurrentVoltageCurve.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Current voltage curves\n",
    "\n",
    "This example shows how the Thales I/E software package can be controlled with Python.\n",
    "\n",
    "The [I/E manual](https://doc.zahner.de/manuals/ie.pdf) provides further explanation of this method and explains the settings."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "from thales_remote.connection import ThalesRemoteConnection\n",
    "from thales_remote.script_wrapper import ThalesRemoteScriptWrapper\n",
    "\n",
    "from zahner_analysis.file_import.iss_import import IssImport\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.ticker import EngFormatter"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Establish and initialize \n",
    "\n",
    "The Term software must be started before the script is executed to be able to connect."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "if __name__ == \"__main__\":\n",
    "    zenniumConnection = ThalesRemoteConnection()\n",
    "    zenniumConnection.connectToTerm(\"localhost\", \"ScriptRemote\")\n",
    "        \n",
    "    zahnerZennium = ThalesRemoteScriptWrapper(zenniumConnection)\n",
    "    zahnerZennium.forceThalesIntoRemoteScript()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# I/E output file setup\n",
    "\n",
    "The first step is to set where the measurement data is to be saved. The path must exist otherwise you will get an error."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'OK\\r'"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "    zahnerZennium.setIEOutputPath(r\"C:\\THALES\\temp\\ie\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then it is set that the measurements are named individual.  \n",
    "In the further process, the other two naming types are also configured as examples."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'OK\\r'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "    zahnerZennium.setIENaming(\"individual\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# I/E measurement parameters\n",
    "\n",
    "In the next step, the actual parameters for the measurement method are set.  \n",
    "Alternatively, a rule file could be loaded which sets the parameters for the measurement.\n",
    "\n",
    "The methods are named after the parameters they set. Additional information can be found in the [API documentation](https://doc.zahner.de/thales_remote/script_wrapper.html)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'OK\\r'"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "    zahnerZennium.calibrateOffsets()\n",
    "    \n",
    "    zahnerZennium.setIEFirstEdgePotential(0)\n",
    "    zahnerZennium.setIEFirstEdgePotentialRelation(\"absolute\")\n",
    "    zahnerZennium.setIESecondEdgePotential(0.4)\n",
    "    zahnerZennium.setIESecondEdgePotentialRelation(\"absolute\")\n",
    "    zahnerZennium.setIEThirdEdgePotential(-0.4)\n",
    "    zahnerZennium.setIEThirdEdgePotentialRelation(\"absolute\")\n",
    "    zahnerZennium.setIEFourthEdgePotential(0)\n",
    "    zahnerZennium.setIEFourthEdgePotentialRelation(\"absolute\")\n",
    "    \n",
    "    zahnerZennium.setIEPotentialResolution(0.005)\n",
    "    zahnerZennium.setIEMinimumWaitingTime(0.1)\n",
    "    zahnerZennium.setIEMaximumWaitingTime(3)\n",
    "    zahnerZennium.setIERelativeTolerance(0.01)  #1 %\n",
    "    zahnerZennium.setIEAbsoluteTolerance(0.001) #1 mA\n",
    "    zahnerZennium.setIEOhmicDrop(0)\n",
    "    \n",
    "    zahnerZennium.setIEScanRate(0.05)\n",
    "    zahnerZennium.setIEMaximumCurrent(3)\n",
    "    zahnerZennium.setIEMinimumCurrent(-3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Execute the measurement\n",
    "\n",
    "In the following, the three different types of I/E are executed one after the other.\n",
    "\n",
    "It also adjusts the file name before each measurement and changes the naming of the files.\n",
    "\n",
    "The [IE manual](https://doc.zahner.de/manuals/ie.pdf) explains the individual types.\n",
    "\n",
    "## Steady State"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'OK\\r'"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "    zahnerZennium.setIESweepMode(\"steady state\")\n",
    "    zahnerZennium.setIEOutputFileName(\"ie_steady\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After checking whether the parameters have been set correctly, the measurement is started."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OK;IESETUP;IE_EckPot1=0.0000e+00;IE_EckPot2=4.0000e-01;IE_EckPot3=-4.0000e-01;IE_EckPot4=0.0000e+00;IE_EckPot1rel=0;IE_EckPot2rel=0;IE_EckPot3rel=0;IE_EckPot4rel=0;IE_Resolution=5.0000e-03;IE_WZmin=0.1;IE_WZmax=3;IE_Torel=1.0000e-02;IE_Toabs=1.0000e-03;IE_Odrop=0.0000e+00;IE_SweepMode=0;IE_Srate=5.0000e-02;IE_Imi=-3.0000e+00;IE_Ima=3.0000e+00;ENDSETUP\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'IE DONE\\r'"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "    zahnerZennium.checkIESetup()\n",
    "    print(zahnerZennium.readIESetup())\n",
    "    \n",
    "    zahnerZennium.measureIE()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dynamic Scan\n",
    "\n",
    "The names of the measurement results are extended with date and time."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OK;IESETUP;IE_EckPot1=0.0000e+00;IE_EckPot2=4.0000e-01;IE_EckPot3=-4.0000e-01;IE_EckPot4=0.0000e+00;IE_EckPot1rel=0;IE_EckPot2rel=0;IE_EckPot3rel=0;IE_EckPot4rel=0;IE_Resolution=5.0000e-03;IE_WZmin=0.1;IE_WZmax=3;IE_Torel=1.0000e-02;IE_Toabs=1.0000e-03;IE_Odrop=0.0000e+00;IE_SweepMode=2;IE_Srate=5.0000e-02;IE_Imi=-3.0000e+00;IE_Ima=3.0000e+00;ENDSETUP\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'IE DONE\\r'"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "    zahnerZennium.setIESweepMode(\"dynamic scan\")\n",
    "    zahnerZennium.setIEOutputFileName(\"ie_dynamic\")\n",
    "    \n",
    "    zahnerZennium.checkIESetup()\n",
    "    print(zahnerZennium.readIESetup())\n",
    "    \n",
    "    zahnerZennium.measureIE()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fixed Sampling\n",
    "\n",
    "The names of the measurement results are extended with date and time."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OK;IESETUP;IE_EckPot1=0.0000e+00;IE_EckPot2=4.0000e-01;IE_EckPot3=-4.0000e-01;IE_EckPot4=0.0000e+00;IE_EckPot1rel=0;IE_EckPot2rel=0;IE_EckPot3rel=0;IE_EckPot4rel=0;IE_Resolution=5.0000e-03;IE_WZmin=0.1;IE_WZmax=3;IE_Torel=1.0000e-02;IE_Toabs=1.0000e-03;IE_Odrop=0.0000e+00;IE_SweepMode=1;IE_Srate=5.0000e-02;IE_Imi=-3.0000e+00;IE_Ima=3.0000e+00;ENDSETUP\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'IE DONE\\r'"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "    zahnerZennium.setIESweepMode(\"fixed sampling\")\n",
    "    zahnerZennium.setIEOutputFileName(\"ie_fixed\")\n",
    "    \n",
    "    zahnerZennium.checkIESetup()\n",
    "    print(zahnerZennium.readIESetup())\n",
    "    \n",
    "    zahnerZennium.measureIE()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Disconnect"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "    zenniumConnection.disconnectFromTerm()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Plotting an IE measurement\n",
    "\n",
    "With the [zahner_analysis](https://pypi.org/project/zahner-analysis/) Python package, the I/E measurements can also be read in for further processing.\n",
    "\n",
    "Here the measurement data are plotted as an example.\n",
    "\n",
    "In this example the measurement data is loaded from a file, but it is also possible to process the data via the remote file interface directly after the measurement in Python. There is also an [example of this using impedance spectra](https://github.com/Zahner-elektrik/Thales-Remote-Python/blob/main/Examples/FileExchangeEIS/FileExchangeEIS.ipynb)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "    measurementData = IssImport(r\"C:\\THALES\\temp\\ie\\ie_steady.iss\")\n",
    "\n",
    "\n",
    "    fig, (axis) = plt.subplots(1, 1)\n",
    "    axis.semilogy(measurementData.getVoltageArray(), abs(measurementData.getCurrentArray()), color = \"red\")\n",
    "    \n",
    "    axis.grid(which=\"both\")\n",
    "    axis.xaxis.set_major_formatter(EngFormatter(unit=\"V\"))\n",
    "    axis.yaxis.set_major_formatter(EngFormatter(unit=\"A\"))\n",
    "    axis.set_xlabel(r\"Voltage\")\n",
    "    axis.set_ylabel(r\"Current\")\n",
    "    fig.set_size_inches(10, 10)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "finish\n"
     ]
    }
   ],
   "source": [
    "    print(\"finish\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.10.5 64-bit",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.5 (tags/v3.10.5:f377153, Jun  6 2022, 16:14:13) [MSC v.1929 64 bit (AMD64)]"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "26de051ba29f2982a8de78e945f0abaf191376122a1563185a90213a26c5da77"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}